Maintain Data Integrity and Protection of Private Label Information in Social Network Data

Perceptive information about users of the social networks should be protected. The confront is to plan methods to publish social network data in a form that affords usefulness without compromising privacy. Previous research has proposed a variety of privacy models with the corresponding protection mechanisms that put off both unintentional private information escape and attacks by malicious adversaries. These early privacy models are mainly disturbed with identity and link revelation. The social networks are modelled as graphs in which users are nodes and social connections are edges.